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Everything about Parameterized approximation algorithm
Type of algorithm
A parameterized approximation algorithm is a type of algorithm that aims to find approximate solutions to NP-hard optimization problems in polynomial time in the input size and a function of a specific parameter. These algorithms are designed to combine the best aspects of both traditional approximation algorithms and fixed-parameter tractability. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Parameterized approximation algorithmA 5-minute orientation
- Skim a recent paper: Parameterized approximation algorithms for weighted vertex coverInfluential work since 2022
- Pick up a classic book: Dynamic General Equilibrium ModellingThe most-reprinted book on the subject
- Read the landmark paper: Parameterized Complexity and Approximation AlgorithmsCited 169 times
- Go sideways: Highway dimensionA closely related topic
- Go sideways: Polynomial-time approximation schemeA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Parameterized Complexity and Approximation Algorithms
A Survey on Approximation in Parameterized Complexity: Hardness and Algorithms
A parameterized approximation algorithm for the mixed and windy capacitated arc routing problem: Theory and experiments
An improved approximation algorithm for the ATSP with parameterized triangle inequality
Parameterized Approximation Algorithms for Bidirected Steiner Network Problems
Parameterized and Approximation Algorithms for the Load Coloring Problem
Parameterized Approximation Algorithms for Sum of Radii Clustering and Variants
A Parameterized Approximation Algorithm for the Chromatic k-Median Problem
🆕 Influential since 2022
Parameterized approximation algorithms for weighted vertex cover
Parameterized Approximation Algorithms for K-center Clustering and Variants
p-Edge/vertex-connected vertex cover: Parameterized and approximation algorithms
On parameterized approximation algorithms for balanced clustering
An improved two-stage approximation algorithm for the k-supplier problem with parameterized triangle inequality
📚 Books worth reading
Dynamic General Equilibrium ModellingBurkhard Heer, Alfred Maussner · 2005
Neuro-fuzzy and soft computingJyh-Shing Roger Jang, Chuen-Tsai Sun · 1996
Experimental AlgorithmsVincenzo Bonifaci · 2013
Computational Intelligence and Decision MakingAna Madureira · 2012
Emerging Technologies for Information Systems, Computing, and ManagementW. Eric Wong · 2013
Linguistic structure predictionNoah A. Smith · 2011
Graph-Theoretic Concepts in Computer ScienceMartin Charles Golumbic · 2012
Advanced Methods, Techniques, and Applications in Modeling and SimulationJong-Hyun Kim · 2012
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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- Polynomial-time approximation scheme In computer science (particularly algorithmics), a polynomial-time approximation scheme (PTAS) is a type of approximation algorithm for optimization problems…
- Steiner tree problem In combinatorial mathematics, the Steiner tree problem, or minimum Steiner tree problem, named after Jakob Steiner, is an umbrella term for a class of…
- Metric k-center In graph theory, the metric k-center problem or vertex k-center problem is a classical combinatorial optimization problem studied in theoretical computer…
- Parameterized complexity In computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according…
- Minimum k-cut In mathematics, the minimum k-cut is a combinatorial optimization problem that requires finding a set of edges whose removal would partition the graph…
- Maximum cut In a graph, a maximum cut is a cut whose size is at least the size of any other cut. That is, it is a partition of the graph's vertices into two complementary…
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